Words that Matter: The Impact of Negative Words on News Sentiment and Stock Market Index

arXiv:2304.00468v2 Announce Type: replace
Abstract: This study investigates the impact of negative words on sentiment analysis and its effect on the South Korean stock market index, KOSPI200. The research analyzes a dataset of 45,723 South Korean daily economic news articles using Word2Vec, cosine similarity, and an expanded lexicon. The findings suggest that incorporating negative words significantly increases sentiment scores' negativity in news titles, which can affect the stock market index. The study reveals that an augmented sentiment lexicon (Sent1000), including …

abstract analysis articles arxiv cs.cl daily dataset economic impact index market matter negative research sentiment sentiment analysis stock study type word2vec words